Contents

• Abstract
• Resolution
• Proposed Solution
• Rationale
• Semantics
• Examples
• Implementation
• Copyright

Abstract

PEP 202 introduces a syntactical extension to Python called the “list comprehension”. This PEP proposes a similar syntactical extension called the “dictionary comprehension” or “dict comprehension” for short. You can use dict comprehensions in ways very similar to list comprehensions, except that they produce Python dictionary objects instead of list objects.

Resolution

This PEP was originally written for inclusion in Python 2.3. It was withdrawn after observation that substantially all of its benefits were subsumed by generator expressions coupled with the dict() constructor.

However, Python 2.7 and 3.0 introduces this exact feature, as well as the closely related set comprehensions. On 2012-04-09, the PEP was changed to reflect this reality by updating its Status to Accepted, and updating the Python-Version field. The Open Questions section was also removed since these have been long resolved by the current implementation.

Proposed Solution

Dict comprehensions are just like list comprehensions, except that you group the expression using curly braces instead of square braces. Also, the left part before the for keyword expresses both a key and a value, separated by a colon. The notation is specifically designed to remind you of list comprehensions as applied to dictionaries.

Rationale

There are times when you have some data arranged as a sequences of length-2 sequences, and you want to turn that into a dictionary. In Python 2.2, the dict() constructor accepts an argument that is a sequence of length-2 sequences, used as (key, value) pairs to initialize a new dictionary object.

However, the act of turning some data into a sequence of length-2 sequences can be inconvenient or inefficient from a memory or performance standpoint. Also, for some common operations, such as turning a list of things into a set of things for quick duplicate removal or set inclusion tests, a better syntax can help code clarity.

As with list comprehensions, an explicit for loop can always be used (and in fact was the only way to do it in earlier versions of Python). But as with list comprehensions, dict comprehensions can provide a more syntactically succinct idiom that the traditional for loop.

Semantics

The semantics of dict comprehensions can actually be demonstrated in stock Python 2.2, by passing a list comprehension to the built-in dictionary constructor:

>>> dict([(i, chr(65+i)) for i in range(4)])

is semantically equivalent to:

>>> {i : chr(65+i) for i in range(4)}

The dictionary constructor approach has two distinct disadvantages from the proposed syntax though. First, it isn’t as legible as a dict comprehension. Second, it forces the programmer to create an in-core list object first, which could be expensive.

Examples

>>> print {i : chr(65+i) for i in range(4)}
{0 : 'A', 1 : 'B', 2 : 'C', 3 : 'D'}

>>> print {k : v for k, v in someDict.iteritems()} == someDict.copy()
1

>>> print {x.lower() : 1 for x in list_of_email_addrs}
{'barry@zope.com'   : 1, 'barry@python.org' : 1, 'guido@python.org' : 1}

>>> def invert(d):
...     return {v : k for k, v in d.iteritems()}
...
>>> d = {0 : 'A', 1 : 'B', 2 : 'C', 3 : 'D'}
>>> print invert(d)
{'A' : 0, 'B' : 1, 'C' : 2, 'D' : 3}

>>> {(k, v): k+v for k in range(4) for v in range(4)}
... {(3, 3): 6, (3, 2): 5, (3, 1): 4, (0, 1): 1, (2, 1): 3,
   (0, 2): 2, (3, 0): 3, (0, 3): 3, (1, 1): 2, (1, 0): 1,
   (0, 0): 0, (1, 2): 3, (2, 0): 2, (1, 3): 4, (2, 2): 4, (
   2, 3): 5}

Implementation

All implementation details were resolved in the Python 2.7 and 3.0 time-frame.

Copyright

This document has been placed in the public domain.